基于BP神经网络的水下岩溶地层#br# 盾构掘进参数预测与分析

随着我国城市地铁网的建设，越来越多的隧道将不可避免的穿越水下岩溶区，受制于岩溶地层的复杂性、注浆加固后地层的诸多不确定性，盾构穿越该类地层施工风险极大，而选取合理的盾构掘进参数是确保盾构安全与高效掘进的关键。以长沙地铁三号线盾构穿越水下岩溶段为工程依托，首先通过统计与分析钻探数据，明确了岩溶分布特征；其次，通过输入地层特征参数和隧道特征参数，建立了可输出盾构掘进速度、推力、刀盘扭矩、开挖仓压力、气垫仓压力和同步注浆量等掘进参数的BP神经网络水下岩溶盾构掘进参数预测模型；最后，对样本数据进行了训练，并成功应用于工程实践。研究结果表明：训练的输出值与期望值吻合度较高，构建的BP神经网络模型具有较好的适应性；输出的预测结果能有效反映实际盾构掘进参数的变化趋势，预测值与实际期望值的平均误差均低于13%，在误差可接受范围内。现场应用结果表明，地表沉降在安全范围内，盾构掘进过程中未发生工程事故，盾构掘进参数选取合理，姿态控制较好。研究成果可用于指导水下岩溶盾构隧道工程施工，且该方法的提出也为其他复杂地层盾构掘进参数合理选取提供了新思路。

Prediction and analysis of shield tunneling parameters in #br# underwater karst stratum based on BP neural network

With the construction of urban subway network in our country, more and more tunnels will inevitably cross the underwater karst area. Restricted by the complexity of karst stratum and many uncertainties of stratum after grouting reinforcement, the construction risk of shield crossing such stratum is high, while the selection of reasonable shield tunneling parameters is the key to ensure the safety and efficiency of shield tunneling. Based on the project of Changsha Metro Line 3 shield passing through the underwater karst section, firstly, the karst distribution characteristics were defined by statistics and analysis of drilling data. Secondly, by inputting the stratum characteristic parameters and tunnel characteristic parameters, the BP neural network was established which can output the shield tunneling speed, thrust, cutter head torque, excavation chamber pressure, air cushion chamber pressure and synchronous grouting amount. Finally, the sample data was trained and successfully applied to engineering practice. The results show that the output value of the training is in good agreement with the expected value, and the BP neural network model has good adaptability; the output prediction results can effectively reflect the change trend of the actual shield tunneling parameters, and the average error between the predicted value and the actual expected value is less than 13%, which is within the acceptable error range. The results of field application show that the ground settlement is within the safe range, no engineering accident occurs in the process of shield tunneling, the selection of shield tunneling parameters is reasonable, and the attitude control is good. The research results can be used to guide the construction of underwater karst shield tunnel, and the proposed method also provides a new idea for the reasonable selection of shield tunneling parameters in other complex strata.